Latin America Intelligent Age

includes planning for responsible land, water and energy use. Emerging advances in AI efficiency, as highlighted in the World Economic Forum’s AI Energy Paradox report, can also help reduce the energy footprint of these systems, supporting more sustainable and inclusive infrastructure growth.53 3. Build universal connectivity Addressing persistent connectivity and device access gaps remains essential to ensure equitable participation in the AI economy across Latin America. Delivery of AI systems relies on fixed wireless, accelerated 5G and robust fibre backbones, as well as last-mile solutions to reach underserved urban and rural areas. Cutting-edge systems, such as LEO satellites, can complement these efforts by extending access to remote regions. Annual scorecards that set measurable targets for coverage and rural gap closure, with quality tracked by speed, latency and device affordability, can link investment to adoption and productivity. 4. Create foundations for data and governance Effective AI depends on easily available, high-quality, interoperable data under clear accountability. Latin America could increase access to open data by creating standardized national portals hosting data segmented by sector. These portals could be complemented by consistent privacy and data-sharing regulations that enable safe flows of data within and across borders, including common schemas, audit checklists and anonymization templates using multilingual standards that reflect Indigenous languages. Companies should ensure their own data foundations are in place as the basic ingredient for the successful implementation of AI. True value creation will depend on consistent, high-quality data. 5. Adapt and implement frontier AI technologies to local needs A key element of accelerating Latin America’s competitiveness in AI will be to focus on applying frontier technologies to the region’s context. Advanced economies outside of the region dominate in building foundational models, semiconductors and other resource-intensive AI technology. To compete, Latin American countries can adapt existing technologies (for example, open source) for priority sectors, benefitting individuals and organizations and driving faster impact. By partnering with global leaders to access cutting-edge tools and fine-tuning them with local data, countries can accelerate deployment and address local challenges at lower cost. To succeed, partnerships should move beyond one-off transfers of knowledge towards joint research initiatives, talent-building programmes and shared technical standards. This approach enables the region to better capture the benefits of global AI while concentrating resources where they deliver the most impact.C Provide clear paths to develop talent 6. Develop AI literacy in education systems and continuous learning opportunities To grow a dynamic talent pipeline in Latin America, it is important to build both foundational and advanced AI knowledge. Curricula should teach core technical and adaptability skills across all education levels. This can help both prepare emerging talent for the AI-centred future of work and provide continuous learning opportunities for the current workforce. Education systems could embed AI literacy and data science at all levels, complemented by scholarships and job placements in research labs and other government and private sector roles. Public funding for R&D centres and AI excellence initiatives can further strengthen this pipeline by expanding opportunities for hands-on learning and research locally, helping emerging talent develop skills without needing to leave the region. Outside of formal education, the current landscape for upskilling and lifelong learning is fragmented. Workforces face difficulties understanding where to invest their time for professional development in AI, and companies can find it hard to discern which AI skills potential talent possess. To address this, countries could collaborate with universities and other institutions to standardize AI credentialing. This would enhance transparency around acquired skills, streamline the hiring process and give a clearer path to employment. D Enable trust, capital and coordination 7. Establish AI ethics and safety regimes Public confidence in AI depends on clear governance. Governments in Latin America could co-design harmonized regulation and frameworks, leveraging regional institutions, public–private partnerships and academia to ensure rules are both technically sound and practical to implement. To streamline this process, countries could align with widely accepted international principles and frameworks, such as those from UNESCO and the OECD. As shown in the Forum’s playbook Advancing Responsible AI Innovation, global initiatives like the Hiroshima AI Process build on these principles and provide a practical framework the region can adopt to reduce fragmentation and ensure consistent, trustworthy governance.54 Such frameworks can incorporate recommendations for both organizations and governments on strategy and value creation, governance and accountability, and development and use. Latin America in the Intelligent Age: A New Path for Growth 25